Description

You lead the validation and migration of machine learning models between Java and Python ecosystems.

This role is remote.

Responsibilities

• Interpret data transformation logic and validate feature pipelines from existing Java implementations.
• Run Python-converted models on historical datasets and validate output metrics against Java model benchmarks.
• Ingest model input data from parquet files using PySpark and pandas to reproduce training and scoring workflows.
• Collaborate with model validation teams to review performance, consistency, and explain metric deviations.
• Design unit tests and validation scenarios to support each migrated model’s readiness for signoff.

Required Skills

• 7+ years of hands-on experience with Python for machine learning.
• Expertise in XGBoost, scikit-learn, NumPy, and pandas.
• Proficiency in PySpark for reading, transforming, and analyzing large parquet datasets.
• Experience validating or reverse engineering ML models from business logic or legacy code.
• Understanding of Java-based ML libraries or how internals map across languages.
• Hands-on experience with Python frameworks for meta-modelling libraries.

Preferred Skills

• Familiarity with Java environments relevant to ML model internals.

Key Skills

Education

Any Graduate